Predicting Unplanned Intubations in Rib Fracture Patients: An Interpretable Machine Learning Approach.
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| Title: | Predicting Unplanned Intubations in Rib Fracture Patients: An Interpretable Machine Learning Approach. |
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| Authors: | Harry SC; University of South Florida Morsani College of Medicine, Tampa, FL, USA., Kendall MA; Department of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL, USA., Grimsley EA; Department of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL, USA., Wolansky RL; Department of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL, USA., Torikashvili JV; University of South Florida Morsani College of Medicine, Tampa, FL, USA., Boughanem D; University of South Florida Morsani College of Medicine, Tampa, FL, USA., Liang Y; University of South Florida Morsani College of Medicine, Tampa, FL, USA., Parikh R; Department of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL, USA., Sujka J; Department of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL, USA., Kuo PC; Department of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL, USA.; Bay Pines Veterans Affairs Health Care System, Bay Pines, FL, USA., Zander T; Department of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL, USA. |
| Source: | The American surgeon [Am Surg] 2026 Jan; Vol. 92 (1), pp. 186-192. Date of Electronic Publication: 2025 Jul 03. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: SAGE Publications in association with Southeastern Surgical Congress Country of Publication: United States NLM ID: 0370522 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1555-9823 (Electronic) Linking ISSN: 00031348 NLM ISO Abbreviation: Am Surg Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1555-9823 |
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| DOI: | 10.1177/00031348251358446 |
